Chinese Restaurant Research Articles

Bayesian spatial homogeneity pursuit for survival data with an application to the SEER respiratory cancer data.

In this work, we propose a new Bayesian spatial homogeneity pursuit method for survival data under the proportional hazards model to detect spatially clustered patterns in baseline hazard and regression coefficients. Specially, regression coefficients and baseline hazard are assumed to have spatial homogeneity pattern over space. To capture such homogeneity, we develop a geographically weighted Chinese restaurant process prior to simultaneously estimating coefficients and baseline hazards and their uncertainty measures. An efficient Markov chain Monte Carlo (MCMC) algorithm is designed for our proposed methods. Performance is evaluated using simulated data, and further applied to a real data analysis of respiratory cancer in the state of Louisiana.

Competing growth processes with random growth rates and random birth times

Comparing individual contributions in a strongly interacting system of stochastic growth processes can be a very difficult problem. This is particularly the case when new growth processes are initiated depending on the state of previous ones and the growth rates of the individual processes are themselves random. We propose a novel technique to deal with such problems and show how it can be applied to a broad range of examples where it produces new insight and surprising results. The method relies on two steps: In the first step, which is highly problem dependent, the growth processes are jointly embedded into continuous time so that their evolutions after initiation become approximately independent while we retain some control over the initiation times. Once such an embedding is achieved, the second step is to apply a Poisson limit theorem that enables a comparison of the state of the processes initiated in a critical window and therefore allows an asymptotic description of the extremal process. In this paper we prove a versatile limit theorem of this type and show how this tool can be applied to obtain novel asymptotic results for a variety of interesting stochastic processes. These include (a) the maximal degree in different types of preferential attachment networks with fitnesses like the well-known Bianconi–Barabási tree and a network model of Dereich, (b) the most successful mutant in branching processes evolving by selection and mutation, and (c) the ratio between the largest and second largest cycles in a random permutation with random cycle weights, which can also be interpreted as a disordered version of Pitman’s Chinese restaurant process.

Lifelong Incremental Reinforcement Learning With Online Bayesian Inference.

A central capability of a long-lived reinforcement learning (RL) agent is to incrementally adapt its behavior as its environment changes and to incrementally build upon previous experiences to facilitate future learning in real-world scenarios. In this article, we propose lifelong incremental reinforcement learning (LLIRL), a new incremental algorithm for efficient lifelong adaptation to dynamic environments. We develop and maintain a library that contains an infinite mixture of parameterized environment models, which is equivalent to clustering environment parameters in a latent space. The prior distribution over the mixture is formulated as a Chinese restaurant process (CRP), which incrementally instantiates new environment models without any external information to signal environmental changes in advance. During lifelong learning, we employ the expectation-maximization (EM) algorithm with online Bayesian inference to update the mixture in a fully incremental manner. In EM, the E-step involves estimating the posterior expectation of environment-to-cluster assignments, whereas the M-step updates the environment parameters for future learning. This method allows for all environment models to be adapted as necessary, with new models instantiated for environmental changes and old models retrieved when previously seen environments are encountered again. Simulation experiments demonstrate that LLIRL outperforms relevant existing methods and enables effective incremental adaptation to various dynamic environments for lifelong learning.

Nonparametric Bayesian background estimation for hyperspectral anomaly detection

We propose an anomaly detection algorithm based on nonparametric Bayesian (NB) background estimation for hyperspectral images. The background is modeled as a Gaussian mixture model (GMM) and the model parameters and order are estimated from the data in an unsupervised manner using nonparametric Bayesian methods called Chinese restaurant process mixtures (CRPM) and truncated Dirichlet process mixtures (TDPM). Since, in anomaly detection, the model parameters are estimated only using the background data in an unsupervised manner, we also propose to use a superpixel-based background data preparation method to obtain a slightly purified background data. In the proposed mixture models, the covariance matrix estimation problem is regularized by defining some conjugate priors to avoid obtaining an ill-conditioned covariance matrix. Finally, the GMM model whose parameters and model order are estimated by the proposed methods is used for anomaly detection. We compare the performances of the proposed methods with those of variational Bayesian, conventional GMM, and collaborative representation-based detector (CRD). Experiments on real hyperspectral data sets show that the proposed methods outperform the detection performance of the other methods.

포스트 코로나 시대의 하이디라오 경쟁우위 지속성에 대한 함의

This paper This paper examines the sources of competitive advantage that Chinese hot pot restaurant company Haidilao has emerged as the number one in the industry despite its less than 30 years of history in terms of differentiation, cost advantage, and resource compliance. We looked at the implications of the sustainability of the existing competitive advantage of Haidilao, whose business environment remains uncertain due to the prolonged crisis due to the COVID-19 pandemic. As a result of the study, Haidilao has a price advantage through quantitative top-line growth through expansion of the number of stores and systematic supply chain management. In addition, under an organizational culture that places great importance on employee satisfaction, a system of active delegation of authority to employees, training and management of human resources, and a fair and fair work environment such as ‘I can change my destiny with my two hands’ are established to continuously gain competitive advantage. Is leading. This was remarkable in terms of customer satisfaction and creating customer value through Hadilao unique excellent service. As an implication, this study aims to provide important information for strategic decision-making to related managers by suggesting ways to secure a competitive advantage for foreign franchise restaurant companies that have entered China in the post-COVID-19 era.

Does Customer Orientation Matter? Direct and Indirect Effects in a Service Quality-Sustainable Restaurant Satisfaction Framework in China

This study aims to further understand the moderating role of customer orientation in the formation of customer satisfaction in the Chinese restaurant context. The first finding of direct effects reveals that customer orientation has a positive impact on quality evaluations, restaurant image and customer satisfaction. Taken in sequence, customer orientation improves quality evaluations, which, in turn, improves restaurant image and customer satisfaction. In particular, restaurant image by itself is not significant in its impact on customer satisfaction, whereas higher levels of customer orientation moderate to strengthen the relationship of restaurant image with customer satisfaction. The authors then provide a managerial framework that can be used to guide customer orientation improvement efforts.

MARKETPLACE CHINESE FOOD DENGAN SISTEM REKOMENDASI MENGGUNAKAN ITEM-BASED COLLABORATIVE FILTERING

Chinese food (typical Chinese cuisine) which is one of the most popular foods in the world. Almost all over the earth, there are always residing Chinese restaurants. Along with the development of culinary in Indonesia, Chinese food restaurant owners began to carry out certain specifications on the menus on offer. As customers will definitely be confused in the choice of food, when the Restaurants have more than one menu. Therefore we need a Marketplace with a recommendation system with the Item-based Collaborative Filtering method. Marketplace is an inter-organizational information system where buyers and sellers in the market communicate information about prices, products and are able to complete transactions via electronic communication channels. There are several stages in using this method, based on first assessing the data, then entering the calculation phase of the similarity between items and then calculating the prediction of item ratings for users.

High-Quality Service in a Chinese Restaurant Chain:

High-Quality Service in a Chinese Restaurant Chain:

I Do So, Like Durian

Where does racism come from? How do experiences with other cultures change our views of race? In this work of philosophical short fiction, Holly, a young teenage girl, heads into Chinatown against her mother’s wishes to visit Jon, a teenage boy, she is interested in dating. He is working at his parents’ Chinese restaurant. She has taken public transportation to Chinatown with her mother knowing, and against her mother’s wishes. Her mother has a strong bias against the area and the people. Holly gets off the bus at the wrong place and gets lost, but friendly locals direct her the right way. She is amazed by the differences in food and culture she sees all around her and ends up buying a durian. Eventually, she finds the restaurant (still carrying the durian), and finds Jon working. Jon is surprised and slightly embarrassed to see Holly and explains to her she will not like taste of the durian. Holly is warmly welcomed by one of Jon’s relatives in the restaurant who agrees to take her in the back and show her out to prepare her exotic fruit.

Longevity: The Archaeology of a Chinese Gift Store and Restaurant in Eugene, Oregon's, Market District

Longevity: The Archaeology of a Chinese Gift Store and Restaurant in Eugene, Oregon's, Market District

Longevity: The Archaeology of a Chinese Gift Store and Restaurant in Eugene, Oregon's, Market District

Longevity: The Archaeology of a Chinese Gift Store and Restaurant in Eugene, Oregon's, Market District

A Pitman-Yor Process Self-Aggregated Topic Model for Short Texts of Social Media

In recent years, with the rapid growth of social media, short texts have been very prevalent on the internet. Due to the limited length of each short text, word co-occurrence information in this type of documents is sparse. Conventional topic models based on word co-occurrence are unable to distill coherent topics on short texts. A state-of-the-art strategy is self-aggregated topic models which implicitly aggregate short texts into latent long documents. But these models have two problems. One problem is that the number of long documents should be defined explicitly and the inappropriate number leads to poor performance. Another problem is that latent long documents may bring non-sematic word co-occurrence which brings incoherent topics. In this article, we firstly apply the Chinese restaurant process to automatically generate the number of long documents according to the scale of short texts. Then to exclude non-semantic word co-occurrence, we propose a novel probabilistic model generating latent long documents in a more semantically way. Specifically, our model employs a pitman-yor process to aggregate short texts into long documents. This stochastic process can guarantee that the distribution between short texts and long documents following a power-law distribution which can be found in social media like Twitter. Finally, we compared our method with several state-of-the-art methods on four real short texts corpus. The experiment results show that our model performs superior to other methods with the metrics of topic coherence and text classification.

Analysis of Monosodium Glutamate (MSG) & Formaldehyde as Food Additives in Swiss Albino Mice Via Experimental Biology: New Version of Modified Analysis

Monosodium Glutamate (MSG) and Formaldehyde, two food additives were taken to access their genotoxicity (in vivo) in Swiss albino mice. Firstly, Swiss albino mice were exposed to different doses of these two food additives. The doses were given intraperitoneally. Bone marrow cells were analyzed for chromosomal aberrations. Different types of aberrations recorded were chromatid break, additions, deletions, ring chromosome, pulverization etc. Because of these aberrations it has been contended that these additives could inflict chromosomal lesions causing defective genetic configuration (Figures 1-5). Monosodium glutamate (MSG) is one of several forms of glutamic acid found in foods, in large part because glutamic acid (an amino acid) is pervasive in nature. MSG is used in the food industry as a flavor enhancer .MSG has been used for more than 100 years to season food, with a number of studies conducted on its safety. Under normal conditions, humans can metabolize relatively large quantities of glutamate, which is naturally produced in the gut by exopeptidase enzymes in the course of protein hydrolysis. The median lethal dose (LD50) is between 15 and 18 g/kg body weight in mice and rats, respectively, five times greater than the LD50 of salt (3 g/kg in rats). The use of MSG as a food additive and the natural level of glutamic acid in foods are not toxicological concerns in humans. MSG has been linked with obesity, metabolic disorders, Chinese Restaurant Syndrome, neurotoxic effects and detrimental effects on the reproductive organs shows products containing substances that result in the release of glutamic metabolites after ingestion.

The Classification of the Chinese Restaurant Industry and Based on the classification table of Chinese economic sector

본 연구는 중국 통계국에서 발행한 경제 업종 분류표를 기반으로 외식업 부분을 업종에 맞게 분류하였고 10년간의 변화 동태를 보며 증감 폭을 파악할 수 있었다. 아직 국내에는 소개되지 않은 중국 외식 부문 산업 분류표가 처음으로 소개된 것에 대하여 큰 의의 가 있다. 본 연구의 결과는 다음과 같다. 첫째, 중국 외식 기업체수는 레스토랑 서비스의 경우 2008년도 대비 10년간 기업체수는 3,269개 증가하였으며 상승폭은 15.64% 증가한 것으로 분석된다. 패스트푸드 서비스는 2008년도 대비 10년간 기업체수가 131개 증가 했으며 상승폭은 15.65%증가 하였다. 음료 및 냉·음료 서비스는 2008년도 대비 10년간 29개 증가 했으며 14.36% 증가하였다. 기타음식점의 경우 228개 감소한 것으로 보이고 증감폭은 38.90% 감소하였다. 둘째, 중국 외식 종사자수는 레스토랑 서비스의 경우 10년간 소폭의 감소가 발생한 이유는 앱 을 활용한 배달서비스의 발달로 인원이 감소한 것으로 파악되고 최근 20,30대 연령층의 냉 음료에 대한 선호도가 증가하여 따뜻한 것만 고집하던 차 문화에서 점점 인식의 변화가 생기고 프랜차이즈 기업에서 운영하는 음료점이 늘어남에 따라 종사자도 역시 증가하였다. 셋째, 중국 외식 매출액은 레스토랑 서비스의 경우 2008년도 대비 10년간 매출액은 1.713억 위안 증가하였으며 상승폭은 83.07% 증가한 것으로 분석된다. 패스트푸드 서비스는 2008년도 대비 10년간 매출액은 834.94억위안 증가 했으며 상승폭은 189.21%증가 하였고 음료 및 냉·음료 서비스는 2008년도 대비 10년간 255.43개 증가 했으며 1,496.36% 증가하였다. 또한 기타음식점은 52.7억 위안 증가하였고 72.59% 증가하였다.

Robust Cell Image Segmentation via Improved Markov Random Field Based on a Chinese Restaurant Process Model

In this paper, a segmentation method for cell images using Markov random field (MRF) based on a Chinese restaurant process model (CRPM) is proposed. Firstly, we carry out the preprocessing on the cell images, and then we focus on cell image segmentation using MRF based on a CRPM under a maximum a posteriori (MAP) criterion. The CRPM can be used to estimate the number of clusters in advance, adjusting the number of clusters automatically according to the size of the data. Finally, the conditional iteration mode (CIM) method is used to implement the MRF based cell image segmentation process. To validate our proposed method, segmentation experiments are performed on oral mucosal cell images. The segmentation results were compared with other methods, using precision, Dice, and mean square error (MSE) as the objective evaluation criteria. The experimental results show that our method produces accurate cell image segmentation results, and our method can effectively improve segmentation for the nucleus, binuclear cell, and micronucleus cell. This work will play an important role in cell image recognition and analysis.

Inferring the Allelic Series at QTL in Multiparental Populations.

Multiparental populations (MPPs) are experimental populations in which the genome of every individual is a mosaic of known founder haplotypes. These populations are useful for detecting quantitative trait loci (QTL) because tests of association can leverage inferred founder haplotype descent. It is difficult, however, to determine how haplotypes at a locus group into distinct functional alleles, termed the allelic series. The allelic series is important because it provides information about the number of causal variants at a QTL and their combined effects. In this study, we introduce a fully Bayesian model selection framework for inferring the allelic series. This framework accounts for sources of uncertainty found in typical MPPs, including the number and composition of functional alleles. Our prior distribution for the allelic series is based on the Chinese restaurant process, a relative of the Dirichlet process, and we leverage its connection to the coalescent to introduce additional prior information about haplotype relatedness via a phylogenetic tree. We evaluate our approach via simulation and apply it to QTL from two MPPs: the Collaborative Cross (CC) and the Drosophila Synthetic Population Resource (DSPR). We find that, although posterior inference of the exact allelic series is often uncertain, we are able to distinguish biallelic QTL from more complex multiallelic cases. Additionally, our allele-based approach improves haplotype effect estimation when the true number of functional alleles is small. Our method, Tree-Based Inference of Multiallelism via Bayesian Regression (TIMBR), provides new insight into the genetic architecture of QTL in MPPs.

The random transposition dynamics on random regular graphs and the Gaussian free field

Une permutation donnée, vue comme réunion de cycles disjoints, représente un graphe régulier de degré $2$. Considérons $d$ permutations aléatoires indépendantes, en superposons leurs structures de graphes. Ceci est le modèle de permutation bien connu donnant un (multi-)graphe régulier aléatoire de degré $2d$. Nous considérons un champ $2$-dimensionnel de $d$ permutations indexé par la taille et le temps. La taille de chaque permutation croît selon des processus couplés de restaurants chinois, tandis que chaque permutation évolue dans le temps selon une chaîne de transpositions aléatoires. À travers le modèle de permutation, ceci se projette en une famille à deux paramètres de graphes qui croissent en taille (« dimension ») et qui évoluent en temps. Dans cet ensemble de graphes aléatoires, on observe asymptotiquement une évolution remarquable des petits cycles et des statistiques linéaires des valeurs propres en dimension et en temps. En dimension, il avait été montré par Johnson et Pal (Ann. Probab. 42 (2014) 1396–1437) que les nombres de cycles sont décrits par un champ poissonnien de processus de Yule. Ici, nous donnons une description en dimension et en temps du processus des cycles en termes en termes d’un surface aléatoire poissonnienne, pour tout $d$. Lorsque $d$ tend vers l’infini, les fluctuations des nombres de cycles convergent vers un processus gaussien indexé par la dimension et le temps. Les marginales en dimension se trouvent être le champ libre gaussien, et le processus est stationnaire en temps. Une structure similaire de covariance apparaît dans les fluctuations des valeurs propres du processus des mineurs d’une matrice de Wigner réelle symétrique dont les coordonnées évoluent selon des processus stochastiques stationnaires i.i.d.. Ainsi, cet article décrit un analogue poissonnien d’une dynamique markovienne naturelle sur le champ libre gaussien, et étudie ses propriétés trajectorielles.

DINING ‘ON AND OFF’: FOOD, WELLBEING AND WECHAT USE AMONG OLDER CHINES MIGRANTS IN AUSTRALIA

This study examines how WeChat, one of the most popular Chinese messenger applications installed on smartphone, facilitates the formation of an older Chinese diasporic space that is centered around the self-nurturing diet (yinshi yangsheng) cultural discourse in Australia. Media has traditionally played a crucial role in disseminating yangsheng-related information and knowledge in China (Sun 2016). However, currently literature in older Chinese people’s media consumption mainly focuses on experience and processes within China few have paid attention to surging number of older Chinese who are ageing in a transnational context. Through analysing data collected from eight focused group (12 people each) conducted at a Chinese restaurant in Brisbane, Australia, and examining OCM participants’ WeChat use,it is found that WeChat not only facilitates the formation of an older Chinese social space in Australia but the platform has acted as a self- and mutual-reliance mechanism for OCMs to negotiate and make sense of their biological change of ageing and biographic change of transnational migration.

An investigation of the diners’ brand love in the value co-creation process

Current research marks the first attempt to investigate the precursors and consequences of brand love in the process of service co-creation in the hospitality sector by taking diners' participation and perceived value as antecedents and three types of diners' well-being as the outcomes of brand love in a realistic co-creation setting (a Chinese hotpot cuisine restaurant). Using 500 responses, this study finds that information-seeking, responsible behavior and personal interaction increase perceived value, whereas information-seeking, personal interaction, and perceived value increase brand love. Perceived value mediates the relationships of information seeking, responsible behavior and personal interaction with brand love. Brand love directly effects all dimensions of diners’ well-being, whereas, information-seeking, responsible behavior and personal interaction indirectly impact all dimensions of well-being. Furthermore, self-perceived mastering negatively moderates the participation—perceived value, and participation—brand love relationships.

Concentration in the Generalized Chinese Restaurant Process

The Generalized Chinese Restaurant Process (GCRP) describes a sequence of exchangeable random partitions of the numbers $\{1,\dots ,n\}$ . This process is related to the Ewens sampling model in Genetics and to Bayesian nonparametric methods such as topic models. In this paper, we study the GCRP in a regime where the number of parts grows like nα with α > 0. We prove a non-asymptotic concentration result for the number of parts of size $k=o(n^{\alpha /(2\alpha +4)}/(\log n)^{1/(2+\alpha )})$ . In particular, we show that these random variables concentrate around ckV∗nα where V∗nα is the asymptotic number of parts and ck ≈ k−(1+α) is a positive value depending on k. We also obtain finite-n bounds for the total number of parts. Our theorems complement asymptotic statements by Pitman and more recent results on large and moderate deviations by Favaro, Feng and Gao.